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Abhay Chaturvedi

Researcher at GLA University

Publications -  63
Citations -  165

Abhay Chaturvedi is an academic researcher from GLA University. The author has contributed to research in topics: Computer science & Noise figure. The author has an hindex of 5, co-authored 34 publications receiving 63 citations. Previous affiliations of Abhay Chaturvedi include Rajasthan Technical University.

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Journal ArticleDOI

Grow of Artificial Intelligence to Challenge Security in IoT Application

TL;DR: The usability of artificial intelligence is discussed, the implementation of AI and IoT analytics are systematically examined as a way of enhancing the health system in the IoT model and different AI-based and device algorithms are also explored.
Journal ArticleDOI

Industrial quality healthcare services using Internet of Things and fog computing approach

TL;DR: In this article , an attempt is made to achieve the Quality of Services in Healthcare through IoT and fog computing, considering optimization of one or more of these parameters such as accuracy of data, speed of decision-making, timely treatment, security of data and real-time monitoring and controlling of the health systems, failure handling and quality of life.
Book ChapterDOI

Improved Cuckoo Search with Artificial Bee Colony for Efficient Load Balancing in Cloud Computing Environment

TL;DR: Improved cuckoo search + artificial bee colony (ICSABC) algorithm is proposed in this work, which is bio-inspired load balancing scheduling algorithm for balancing load and results in high accuracy and low complexity time, when compared with existing methods.
Proceedings ArticleDOI

Double Balanced Diode Ring Mixer for Ultra-wideband System

TL;DR: A double balanced diode ring mixer is presented for MB (multiband) UWB (ultra wideband) system and effectively suppresses the harmonic and IMD (inter-modulation) products at IF port.
Journal ArticleDOI

Novel Predictive Control and Monitoring System based on IoT for Evaluating Industrial Safety Measures

TL;DR: In this article , the authors used the Accident Reduction Model (ARM) technique to analyze different critical criteria in various industries, and then used it to determine the conclusions of the decision-making process.